ApptillionEvidence before confidence
Matched fields, score components, source freshness, and the official notice are visible before the numeric score.
Review-ready evidence
Recall screening API
A recall match should showwhy it matched.
An API and CSV workbench that turns messy product rows into explainable recall candidates, visible source coverage, and a safer human-review queue.
- Built for
- Resale marketplaces, consignment teams, and catalog developers
- Domain-ready
- recalllens.apptillion.com
RLRecallLens
sample result86
Result
Possible recall candidate
Brand + product typepass
Model confirmationreview
Official verificationfix
Every conclusion keeps its source, uncertainty, and next human action attached.
A useful result before an account wall
Try the experience.
This is an interactive product preview using illustrative data. It shows the intended decision flow without claiming the processing backend is already live.
private preview · sample data
01
Start with one clear input
sample
No file is uploaded here. A production version would show retention choices before transfer.
The experience advantage
Less anxiety. More visible progress.
The competitors prove the job exists. RecallLens improves the moment between input and decision: uncertainty is reviewable, sources stay attached, and the useful output arrives before a dashboard.
A humane review queue
Reviewers see the missing field to request, not a frightening red badge with no route to resolution.
Cheaper public-source architecture
Local normalized indexes cover routine matching; official APIs and live links remain the verification layer.
The better way
One complete path from input to next action.
- 1
Normalize the row
Clean brands, titles, model numbers, UPCs, lots, and dates without erasing the original input.
- 2
Show candidate evidence
Return field-level reasons, source state, and which identifiers are still missing.
- 3
Route the next action
Continue, request a model or lot, or require a reviewer to open the official recall notice.
Pricing without make-believe
Free where the market is free. Paid where the work continues.
RecallLens proposes $9/5,000 and $29/25,000 calls: roughly 76% and 78% lower per call at the compared tiers.
Explore
$01,000 calls/month
API keys, explainable matches, source state, and a 100-row CSV scan.
Start with the sampleBuilder
$95,000 calls/month
About 76% less per call than CatalogRecall Starter.
Start with the sampleReview queue
$2925,000 calls/month
About 78% less per call than CatalogRecall Developer, plus batch review.
Start with the sampleCompared with
CatalogRecall: $19/2,500 calls and $79/15,000 calls
The trust boundary
Useful preflight, clearly short of approval.
RecallLens performs automated matching against connected public sources. A no-match result never means an item is safe or not recalled.
Validation site, ready for real traffic